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| description: Learn how to set up and customize MLflow logging for Ultralytics YOLO. Log metrics, parameters, and model artifacts easily. |
| keywords: MLflow, Ultralytics YOLO, logging, metrics, parameters, model artifacts, setup, tracking, customization |
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| # Reference for `ultralytics/utils/callbacks/mlflow.py` |
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| !!! Note |
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| This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/callbacks/mlflow.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/callbacks/mlflow.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/utils/callbacks/mlflow.py) 🛠️. Thank you 🙏! |
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| ## ::: ultralytics.utils.callbacks.mlflow.sanitize_dict |
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| <br><br><hr><br> |
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| ## ::: ultralytics.utils.callbacks.mlflow.on_pretrain_routine_end |
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| <br><br><hr><br> |
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| ## ::: ultralytics.utils.callbacks.mlflow.on_train_epoch_end |
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| <br><br><hr><br> |
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| ## ::: ultralytics.utils.callbacks.mlflow.on_fit_epoch_end |
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| <br><br><hr><br> |
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| ## ::: ultralytics.utils.callbacks.mlflow.on_train_end |
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| <br><br> |
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